code: def _build_dataloader(self):
      print("starting build the dataset")
  
      if args.graph_name == "line_graph":
          dataset = ConllDataset(
              root_dir="examples/pytorch/name_entity_recognition/conll",
              topology_builder=LineBasedGraphConstruction,
              graph_name=args.graph_name,
              static_or_dynamic=args.static_or_dynamic,
              pretrained_word_emb_cache_dir=args.pre_word_emb_file,
              topology_subdir="LineGraph",
              tag_types=self.tag_types,
          )
      elif args.graph_name == "dependency_graph":
          dataset = ConllDataset(
              root_dir="examples/pytorch/name_entity_recognition/conll",
              topology_builder=DependencyBasedGraphConstruction_without_tokenizer,
              graph_name=args.graph_name,
              static_or_dynamic="static",
              pretrained_word_emb_cache_dir=args.pre_word_emb_file,
              topology_subdir="DependencyGraph",
              tag_types=self.tag_types,
          )
      elif args.graph_name == "node_emb":
          dataset = ConllDataset(
              root_dir="examples/pytorch/name_entity_recognition/conll",
              topology_builder=NodeEmbeddingBasedGraphConstruction,
              graph_name=args.graph_name,
              static_or_dynamic="static",
              pretrained_word_emb_cache_dir=args.pre_word_emb_file,
              topology_subdir="DynamicGraph_node_emb",
              tag_types=self.tag_types,
              merge_strategy=None,
          )
      elif args.graph_type == "node_emb_refined":
          if args.init_graph_name == "line":
              dynamic_init_topology_builder = LineBasedGraphConstruction
          elif args.init_graph_name == "dependency":
              dynamic_init_topology_builder = (
                  DependencyBasedGraphConstruction_without_tokenizer
              )
          else:
              # init_topology_builder
              raise RuntimeError(
                  "Define your own init_topology_builder"
              )
          dataset = ConllDataset(
              root_dir="examples/pytorch/name_entity_recognition/conll",
              topology_builder=NodeEmbeddingBasedRefinedGraphConstruction,
              graph_name=args.graph_name,
              static_or_dynamic="dynamic",
              pretrained_word_emb_cache_dir=args.pre_word_emb_file,
              topology_subdir="DynamicGraph_node_emb_refined",
              tag_types=self.tag_types,
              dynamic_init_topology_builder=dynamic_init_topology_builder,
              dynamic_init_topology_aux_args={"dummy_param": 0},
          )
  
      print(len(dataset.train))
      print("strating loading the training data")
      self.train_dataloader = DataLoader(
          dataset.train,
          batch_size=args.batch_size,
          shuffle=True,
          num_workers=1,
          collate_fn=dataset.collate_fn,
      )
      print("strating loading the validating data")
      self.val_dataloader = DataLoader(
          dataset.val,
          batch_size=100,
          shuffle=True,
          num_workers=1,
          collate_fn=dataset.collate_fn,
      )
      print("strating loading the testing data")
      self.test_dataloader = DataLoader(
          dataset.test,
          batch_size=100,
          shuffle=True,
          num_workers=1,
          collate_fn=dataset.collate_fn,
      )
      print("strating loading the vocab")
      self.vocab = dataset.vocab_model
  
imports: import argparse
  import os
  import torch
  import torch.backends.cudnn
  import torch.multiprocessing
  import torch.optim
  from torch.utils.data import DataLoader
  from graph4nlp.pytorch.data.data import from_batch
  from graph4nlp.pytorch.modules.evaluation.accuracy import Accuracy
  from graph4nlp.pytorch.modules.graph_construction import NodeEmbeddingBasedRefinedGraphConstruction
  from graph4nlp.pytorch.modules.graph_construction.node_embedding_based_graph_construction import NodeEmbeddingBasedGraphConstruction
  from graph4nlp.pytorch.modules.utils.generic_utils import to_cuda
  from conll import ConllDataset
  from conlleval import evaluate
  from dependency_graph_construction_without_tokenize import DependencyBasedGraphConstruction_without_tokenizer
  from line_graph_construction import LineBasedGraphConstruction
  from model import Word2tag
label_desc: Use image node_id 2 for calling the Conll obj's underlying member method code with example usage: obj._build_dataloader() without return types